Modeling Disease Pathways Through Ventricular Depolarization

Host: Anthony Kashou, MD
Guest: Peter van Dam, Ph.D.

Overview:
Detection of disease progression is hampered due to the large variation in normal QRS morphologies, even for the ECG expert. Cardiac modeling techniques can improve the interpretation and diagnostic value of the ECG by visualizing relevant QRS deviations. Comparing the QRS waveforms and electrical pathway in genetical patients to normal controls shows that even small changes in the QRS can be detected in patients with a genetical disease, like Brugada or ACM.

Questions:
1. What is the PathECG?
The PathECG is a reconstruction of the average position of the electrical activity within the heart. In previous vectorcardiographic research this has also been moving dipole position, i.e. the pathECG is the trajectory of the dipole over time.

2. How do you compare to normal Waveform?
Take 1000's of normal classified ECGs and build a distribution of normal ECGs. When an ECG signal moves outside this normal distribution, teh ECG might be abnormal. This comparison enables simple visual detection of abnormal segments in the QRS per lead.

3. What can the PathECG add to the ECG?
The PathECG does not take the amplitude of the ECG into account, it shows just the path of the electrical activity. Consequently, the PathECG moves toward parts of the heart where the electrical activation is late, i.e. QRS end. In Brugada patients the terminal part of the QRS moves towards the RVOT, the anatomical (epicardial) location where the activation is late. But even when the delay occurs in the middle of the QRS, the PathECG can deviate in the terminal part.
4. Could this improve the quality of the ECG diagnosis?

In a recent study, we used 37 ECGs of asymptomatic PKP2-PV carriers (ARVC/ACM). All ECGs were classified by two experts as ECGs within teh normal range. Using both the comparison waveform and PathECG comparison, showed that in 60% of these ECGs abnormalities could be detected.